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The article discusses a study which described the use of satellite observations and information to track the dynamics of carbon dioxide emissions during COVID-19 pandemic in China. TROPOspheric Monitoring Instrument onboard the Copernicus Sentinel-5 Precursor satellite was employed to observe nitrogen dioxide. Results of the study are discussed. Materials and methods used are described.

In this article the authors discuss the Mauna Loa carbon dioxide (CO2) time series begun by C. D. Keeling in 1958 and maintained by the Scripps Institution of Oceanography and the U.S. National Oceanic and Atmospheric Administration's (NOAA's) Earth System Research Laboratory (ESRL). They discuss the time series' role in providing evidence of the impact of human-induced atmospheric increases of CO2 and the impact of NOAA budget cuts on climate change research.

Response actions to the coronavirus disease 2019 perturbed economies and carbon dioxide (CO 2 ) emissions. The Omicron variant that emerged in 2022 caused more substantial infections than in 2020 and 2021 but it has not yet been ascertained whether Omicron interrupted the temporary post-2021 rebound of CO 2 emissions. Here, using satellite nitrogen dioxide observations combined with atmospheric inversion, we show a larger decline in China's CO 2 emissions between January and April 2022 than in those months during the first wave of 2020. China's CO 2 emissions are estimated to have decreased by 15% (equivalent to -244.3 million metric tons of CO 2 ) during the 2022 lockdown, greater than the 9% reduction during the 2020 lockdown. Omicron affected most of the populated and industrial provinces in 2022, hindering China's CO 2 emissions rebound starting from 2021. China's emission variations agreed with downstream CO 2 concentration changes, indicating a potential to monitor CO 2 emissions by integrating satellite and ground measurements.

Changes in CO 2 emissions during the COVID-19 pandemic have been estimated from indicators on activities like transportation and electricity generation. Here, we instead use satellite observations together with bottom-up information to track the daily dynamics of CO 2 emissions during the pandemic. Unlike activity data, our observation-based analysis deploys independent measurement of pollutant concentrations in the atmosphere to correct misrepresentation in the bottom-up data and can provide more detailed insights into spatially explicit changes. Specifically, we use TROPOMI observations of NO 2 to deduce 10-day moving averages of NO x and CO 2 emissions over China, differentiating emissions by sector and province. Between January and April 2020, China's CO 2 emissions fell by 11.5% compared to the same period in 2019, but emissions have since rebounded to pre-pandemic levels before the coronavirus outbreak at the beginning of January 2020 owing to the fast economic recovery in provinces where industrial activity is concentrated., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).)